Intuition speed as a predictor of choice and confidence in point spread predictions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Previous research has revealed that intuitive confidence is an important predictor of how people choose between an intuitive and non-intuitive alternative when faced with information that opposes the intuitive response. In the current study, we investigated the speed of intuition generation as a predictor of intuitive confidence and participant choice in choice conflict situations. Participants predicted the outcomes of several National Basketball Association games, both with and without reference to a point spread. As hypothesized, the faster participants were to predict the outright winner of a game (i.e., generate an intuition) the more likely they were to predict the favourite against the point spread for that game (i.e., endorse the intuitive response). Overall, our findings are consistent with the notion that the speed of intuition generation acts as a determinant of intuitive confidence and a predictor of choice in situations featuring equally valid intuitive and non-intuitive alternatives.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it